School of Data Science and Artificial Intelligence, Wenzhou University of Technology, Wenzhou, China.
College of Computer Science and Electronic Engineering, Hunan University, Changsha, China.
PLoS Comput Biol. 2024 Aug 30;20(8):e1012400. doi: 10.1371/journal.pcbi.1012400. eCollection 2024 Aug.
The identification of cancer driver genes (CDGs) poses challenges due to the intricate interdependencies among genes and the influence of measurement errors and noise. We propose a novel energy-constrained diffusion (ECD)-based model for identifying CDGs, termed ECD-CDGI. This model is the first to design an ECD-Attention encoder by combining the ECD technique with an attention mechanism. ECD-Attention encoder excels at generating robust gene representations that reveal the complex interdependencies among genes while reducing the impact of data noise. We concatenate topological embedding extracted from gene-gene networks through graph transformers to these gene representations. We conduct extensive experiments across three testing scenarios. Extensive experiments show that the ECD-CDGI model possesses the ability to not only be proficient in identifying known CDGs but also efficiently uncover unknown potential CDGs. Furthermore, compared to the GNN-based approach, the ECD-CDGI model exhibits fewer constraints by existing gene-gene networks, thereby enhancing its capability to identify CDGs. Additionally, ECD-CDGI is open-source and freely available. We have also launched the model as a complimentary online tool specifically crafted to expedite research efforts focused on CDGs identification.
由于基因之间错综复杂的相互依赖关系以及测量误差和噪声的影响，癌症驱动基因（CDG）的鉴定具有挑战性。我们提出了一种新的基于能量约束扩散（ECD）的 CDG 识别模型，称为 ECD-CDGI。该模型是第一个通过将 ECD 技术与注意力机制相结合来设计 ECD-Attention 编码器的模型。ECD-Attention 编码器擅长生成强大的基因表示，揭示基因之间复杂的相互依赖关系，同时减少数据噪声的影响。我们通过图变换将从基因-基因网络中提取的拓扑嵌入与这些基因表示连接起来。我们在三个测试场景中进行了广泛的实验。大量实验表明，ECD-CDGI 模型不仅能够熟练地识别已知的 CDG，而且能够有效地发现未知的潜在 CDG。此外，与基于 GNN 的方法相比，ECD-CDGI 模型受现有基因-基因网络的约束较少，从而提高了其识别 CDG 的能力。此外，ECD-CDGI 是开源的，并且是免费提供的。我们还推出了该模型作为一个补充性的在线工具，专门用于加速 CDG 识别的研究工作。
